Bottom Line:
Excluding 1, 2, and 3 cm of RL near the interface changed the resulting RL [Formula: see text] by -22, -38, and -48 %, respectively, for all VBDM.SK underestimates RL [Formula: see text] relative to MC whereas LD and SKD overestimate.RL [Formula: see text] is strongly influenced by the liver-lung interface.

Background: To assess differences between four different voxel-based dosimetry methods (VBDM) for tumor, liver, and lung absorbed doses following (90)Y microsphere selective internal radiation therapy (SIRT) based on (90)Y bremsstrahlung SPECT/CT, a secondary objective was to estimate the sensitivity of liver and lung absorbed doses due to differences in organ segmentation near the liver-lung interface.

Methods: Investigated VBDM were Monte Carlo (MC), soft-tissue kernel with density correction (SKD), soft-tissue kernel (SK), and local deposition (LD). Seventeen SIRT cases were analyzed. Mean absorbed doses ([Formula: see text]) were calculated for tumor, non-tumoral liver (NL), and right lung (RL). Simulations with various SPECT spatial resolutions (FHWMs) and multiple lung shunt fractions (LSs) estimated the accuracy of VBDM at the liver-lung interface. Sensitivity of patient RL and NL [Formula: see text] on segmentation near the interface was assessed by excluding portions near the interface.

Results: SKD, SK, and LD were within 5 % of MC for tumor and NL [Formula: see text]. LD and SKD overestimated RL [Formula: see text] compared to MC on average by 17 and 20 %, respectively; SK underestimated RL [Formula: see text] on average by -60 %. Simulations (20 mm FWHM, 20 % LS) showed that SKD, LD, and MC were within 10 % of the truth deep (>39 mm) in the lung; SK significantly underestimated the absorbed dose deep in the lung by approximately -70 %. All VBDM were within 10 % of truth deep (>12 mm) in the liver. Excluding 1, 2, and 3 cm of RL near the interface changed the resulting RL [Formula: see text] by -22, -38, and -48 %, respectively, for all VBDM. An average change of -7 % in the NL [Formula: see text] was realized when excluding 3 cm of NL from the interface. [Formula: see text] was realized when excluding 3 cm of NL from the interface.

Conclusions: SKD, SK, and LD are equivalent to MC for tumor and NL [Formula: see text]. SK underestimates RL [Formula: see text] relative to MC whereas LD and SKD overestimate. RL [Formula: see text] is strongly influenced by the liver-lung interface.

Fig4: The correlation of patient absorbed doses from MC with those from LD (green triangles), SK (red squares), and SKD (blue diamonds) for tumor (N = 31) (a), NL (N = 17) (b), and RL (N = 17) (c) shown together with their linear fits. The gray dashed line represents the line of equivalence

Mentions:
The correlations in absorbed dose as estimated using LD, SK, and SKD in relation to the true values from MC are shown in Fig. 4. All the correlations had R2 > 0.975. Slopes of the fit lines ranged from 0.98 to 1.00 for tumors and NL. For RL , the slopes were 0.88, 0.90, and 2.32 for SKD, LD, and SK, respectively. The summary of percent differences relative to MC are listed in Table 2. to tumors and NL using LD, SK, and SKD were within 5 % of MC . For to RL, LD had the best agreement (17 % on average) with MC, whereas SK had the poorest agreement (−60 % on average).Fig. 4

Fig4: The correlation of patient absorbed doses from MC with those from LD (green triangles), SK (red squares), and SKD (blue diamonds) for tumor (N = 31) (a), NL (N = 17) (b), and RL (N = 17) (c) shown together with their linear fits. The gray dashed line represents the line of equivalence

Mentions:
The correlations in absorbed dose as estimated using LD, SK, and SKD in relation to the true values from MC are shown in Fig. 4. All the correlations had R2 > 0.975. Slopes of the fit lines ranged from 0.98 to 1.00 for tumors and NL. For RL , the slopes were 0.88, 0.90, and 2.32 for SKD, LD, and SK, respectively. The summary of percent differences relative to MC are listed in Table 2. to tumors and NL using LD, SK, and SKD were within 5 % of MC . For to RL, LD had the best agreement (17 % on average) with MC, whereas SK had the poorest agreement (−60 % on average).Fig. 4

Bottom Line:
Excluding 1, 2, and 3 cm of RL near the interface changed the resulting RL [Formula: see text] by -22, -38, and -48 %, respectively, for all VBDM.SK underestimates RL [Formula: see text] relative to MC whereas LD and SKD overestimate.RL [Formula: see text] is strongly influenced by the liver-lung interface.

Background: To assess differences between four different voxel-based dosimetry methods (VBDM) for tumor, liver, and lung absorbed doses following (90)Y microsphere selective internal radiation therapy (SIRT) based on (90)Y bremsstrahlung SPECT/CT, a secondary objective was to estimate the sensitivity of liver and lung absorbed doses due to differences in organ segmentation near the liver-lung interface.

Methods: Investigated VBDM were Monte Carlo (MC), soft-tissue kernel with density correction (SKD), soft-tissue kernel (SK), and local deposition (LD). Seventeen SIRT cases were analyzed. Mean absorbed doses ([Formula: see text]) were calculated for tumor, non-tumoral liver (NL), and right lung (RL). Simulations with various SPECT spatial resolutions (FHWMs) and multiple lung shunt fractions (LSs) estimated the accuracy of VBDM at the liver-lung interface. Sensitivity of patient RL and NL [Formula: see text] on segmentation near the interface was assessed by excluding portions near the interface.

Results: SKD, SK, and LD were within 5 % of MC for tumor and NL [Formula: see text]. LD and SKD overestimated RL [Formula: see text] compared to MC on average by 17 and 20 %, respectively; SK underestimated RL [Formula: see text] on average by -60 %. Simulations (20 mm FWHM, 20 % LS) showed that SKD, LD, and MC were within 10 % of the truth deep (>39 mm) in the lung; SK significantly underestimated the absorbed dose deep in the lung by approximately -70 %. All VBDM were within 10 % of truth deep (>12 mm) in the liver. Excluding 1, 2, and 3 cm of RL near the interface changed the resulting RL [Formula: see text] by -22, -38, and -48 %, respectively, for all VBDM. An average change of -7 % in the NL [Formula: see text] was realized when excluding 3 cm of NL from the interface. [Formula: see text] was realized when excluding 3 cm of NL from the interface.

Conclusions: SKD, SK, and LD are equivalent to MC for tumor and NL [Formula: see text]. SK underestimates RL [Formula: see text] relative to MC whereas LD and SKD overestimate. RL [Formula: see text] is strongly influenced by the liver-lung interface.